AIMC Topic: Protein Interaction Maps

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ProteinWeaver: A webtool to visualize ontology-annotated protein networks.

PloS one
Molecular interaction networks are a vital tool for studying biological systems. While many tools exist that visualize a protein or a pathway within a network, no tool provides the ability for a researcher to consider a protein's position in a networ...

Uncovering key biomarkers, potential therapeutic targets and development of deep learning model in heart failure.

PloS one
Heart failure (HF) represents a significant public health concern, characterized by elevated rates of mortality and morbidity. Recent advancements in gene sequencing technologies have led to the identification of numerous genes associated with heart ...

Major pathophysiological changes in pulmonary disease provided a molecular insight based on deep learning approach.

Scientific reports
The outburst of pulmonary disorders among the society has shown the devastating effect of undergoing a delay in diagnosis and treatment. Sometimes the traditional methods in detecting and treating the airway disease fail to cure efficiently due to a ...

Exploring potential associations and biomarkers linked polycystic ovarian syndrome with atherosclerosis via comprehensive bioinformatics analysis, machine learning, and animal experiments.

Functional & integrative genomics
Polycystic ovary syndrome (PCOS), a common endocrine condition affecting multiple systems, is tied to atherosclerosis (AS) progression among reproductive-aged women. The present study aimed to explore the underlying associations and uncover potential...

Mapping a interactome by crosslinking mass spectrometry and machine learning.

mBio
, a widespread human parasite, persists in hosts through complex molecular interactions. Protein-protein interactions (PPIs) underpin essential biological processes, including parasite-host interactions and cellular invasion. Herein, we utilized adva...

Screening of hub genes and immunocytes related to tendon injury based on bioinformatics and machine learning models.

Scientific reports
Tendon injury is a common and challenging clinical problem, and its healing process involves complex cellular and biological factors. Therefore, this study aims to reveal the mechanism of tendon healing and provide theoretical basis for clinical trea...

Revealing potential interfering genes between abdominal aortic aneurysm and periodontitis through machine learning and bioinformatics analysis.

PloS one
This study aimed to identify potential interacting genes between abdominal aortic aneurysm (AAA) and periodontitis. To achieve this, we obtained datasets of AAA and periodontitis from the GEO database, conducted differential analysis on the AAA datas...

Aging associated immunosenescence in rheumatoid arthritis identified by machine learning and single cell profiling.

Scientific reports
Rheumatoid arthritis (RA) is increasingly prevalent among older adults, who often experience more severe symptoms and face significant treatment challenges. This study aims to identify specific genes associated with aging in RA and to analyze their i...

MESM: integrating multi-source data for high-accuracy protein-protein interactions prediction through multimodal language models.

BMC biology
BACKGROUND: Protein-protein interactions (PPIs) play a critical role in essential biological processes such as signal transduction, enzyme activity regulation, cytoskeletal structure, immune responses, and gene regulation. However, current methods ma...

Identifying ferroptosis-related genes in lung adenocarcinoma using random walk with restart in the PPI network.

Scientific reports
Lung adenocarcinoma (LUAD), the most common non-small cell lung cancer subtype, often presents with subtle early symptoms leading to delayed diagnosis. Ferroptosis, a cell death process associated with iron metabolism dysregulation, has been linked t...